A method for breeding a new wheat variety with high resistance to scab

Abstract

The application discloses a method for breeding a new wheat variety with high resistance to scab, which comprises the following steps: selecting wheat varieties carrying different scab-resistant genes for hybridization, rapidly propagating in an artificial intelligent greenhouse, and evaluating the adaptability of the hybrid offspring by simulating ecological conditions in different regions; further, combining the traits of plant height, maturity, yield, disease resistance and adaptability, using a comprehensive evaluation formula to score the hybrid offspring, and carrying out field tests on the hybrid offspring and its parents with the optimal comprehensive evaluation performance, so as to verify the improvement degree of the hybrid offspring in agronomic traits and scab resistance. Through the comprehensive evaluation of the hybrid offspring under different genetic backgrounds, gene combinations and environmental conditions, and through the comprehensive evaluation formula, a comprehensive evaluation system is provided for the breeding of wheat varieties, the comprehensive performance of each combination of hybrid offspring can be directly evaluated, and precise data basis is provided for the breeding of a new wheat variety with high resistance to scab.

Description

Technical Field

[0001] This invention relates to the field of wheat breeding technology, and in particular to a method for breeding new wheat varieties that are highly resistant to Fusarium head blight. Background Technology

[0002] Germplasm resources, as the cornerstone of disease-resistant breeding, play a crucial role in improving the efficiency of genetic improvement of wheat resistance to Fusarium head blight. Researchers are dedicated to achieving breakthroughs in the discovery of new germplasm resistant to Fusarium head blight.

[0003] Although no wheat varieties have yet been found to be completely immune to Fusarium head blight, there are significant differences in resistance among varieties. Some local varieties, such as Wangshui White and Fanshan Wheat, as well as conventional hybrid varieties such as Sumai No. 3 and Ning 7840, have shown moderate to high resistance to Fusarium head blight. However, unfortunately, with the exception of a few varieties from the Yangmai, Ningmai, and Emai series, most varieties are quite susceptible to Fusarium head blight.

[0004] Meanwhile, wheat varieties resistant to Fusarium head blight often have deficiencies in agronomic traits, such as excessively tall plant height, sparse spikelets, and poor plant architecture. These problems limit the practical application of these resistant varieties in agricultural production.

[0005] Therefore, it is necessary to provide a method for breeding new wheat varieties with high resistance to Fusarium head blight in order to solve the above-mentioned technical problems, overcome the shortcomings of existing varieties, improve the resistance of wheat to Fusarium head blight, and at the same time ensure its excellent agronomic traits. Summary of the Invention

[0006] This invention overcomes the shortcomings of the prior art and provides a method for breeding new wheat varieties with high resistance to Fusarium head blight.

[0007] To achieve the above objectives, the technical solution adopted by this invention is as follows: a method for breeding new wheat varieties highly resistant to Fusarium head blight, comprising the following steps:

[0008] S1. Select wheat varieties with different Fusarium head blight resistance genes as parents for crossbreeding;

[0009] S2. Hybridization is carried out in an artificial intelligence greenhouse to obtain the initial F1 generation, and the genotype is gradually purified through continuous self-crossing or backcrossing to obtain genetically stable hybrid offspring.

[0010] S3. Divide the artificial intelligence greenhouse into multiple simulated planting areas. Each planting area simulates the ecological conditions of different regions, including soil conditions, temperature and humidity.

[0011] S4. Based on the genetic background and disease-resistant gene combination of the hybrid offspring, the hybrid offspring in each group are grouped and then assigned to different planting cohorts. These planting cohorts are planted in different planting areas, and data on plant height, maturity, yield and disease resistance of the hybrid offspring in each cohort are collected.

[0012] S5. Based on the data collected in S4 and the environmental conditions of the planting area where each cohort is located, an adaptability evaluation is performed on each group of hybrid offspring, and then a comprehensive evaluation of each group of hybrid offspring is calculated by combining the data collected in S4.

[0013] S6. In the comprehensive evaluation, select several groups of hybrid offspring with the best performance and conduct field trials together with their parents. By comparing the comprehensive evaluation and disease resistance of the parents and corresponding hybrid offspring, select new wheat varieties with significant high resistance to Fusarium head blight.

[0014] In a preferred embodiment of the present invention, in S1, the wheat-ciliad translocation lines NAURc001, Sumai 3, Wangshuibai, Yangmai 33 and Ningmai 9, which are resistant to Fusarium head blight, are used as male / female parents for pairwise hybridization.

[0015] In a preferred embodiment of the present invention, in step S3, the artificial intelligence greenhouse is divided into three areas, which respectively correspond to the simulated northern winter wheat region, the Huang-Huai winter wheat region, and the southwestern winter wheat region.

[0016] In a preferred embodiment of the present invention, in step S4, based on the molecular marker-assisted selection results of the hybrid offspring of step S2, the offspring carrying different combinations of Fusarium head blight resistance genes are divided into different groups. Each group should have a uniform genetic background, and the number of plants in several planting cohorts within the same group should be equal.

[0017] In a preferred embodiment of the present invention, in step S4, the disease resistance data refers to resistance to Fusarium head blight, and the polymer is inoculated with and identified by Fusarium head blight using a single-flower drip method to evaluate its resistance.

[0018] Fusarium head blight resistance is classified into different levels, including: immune, highly resistant, moderately resistant, moderately susceptible, and highly susceptible.

[0019] In a preferred embodiment of the present invention, in step S5, the fitness evaluation of each group of hybrid offspring includes the following steps:

[0020] S51. Calculate the average yield of all hybrid offspring in each planting area;

[0021] S52. Calculate the average Fusarium head blight resistance score of all hybrid offspring in each planting area;

[0022] S53, Adaptability score of each group of hybrid offspring Among them, Y ij D is the yield of hybrid offspring i in the j-th planting area; ij E is the Fusarium head blight resistance score of hybrid offspring i in the j-th planting area; j F is the yield score weight for the j-th planting area; j The disease resistance score weight for the j-th planting area; n is the total number of planting areas.

[0023] In a preferred embodiment of the present invention, in step S5, the plant height, maturity period, yield, and disease resistance indicators of each group of hybrid offspring are scored and determined.

[0024] Plant height is the average plant height H of each group of hybrid offspring. i The scores are divided into four levels: 2 points for 80cm and below, 1 point for 80-85cm, 0 points for 85-90cm, and -1 point for 90cm and above.

[0025] The maturity period is M, which is the average maturity period of each group of hybrid offspring. i The scores are divided into three levels, based on a control group: 1 point for early-maturing varieties, 0 points for equivalent varieties, and -1 point for late-maturing varieties.

[0026] The yield is the total yield P of each group of hybrid offspring. i The yield is divided into three levels: 1 point is awarded for yields of 590kg or more, 0 points are awarded for yields between 540kg and 590kg, and -1 point is awarded for yields of 540kg or less.

[0027] Fusarium head blight resistance is the average resistance F of each hybrid progeny. i The test is divided into five levels: immune, high resistance, moderate resistance, moderate infection, and high infection. Immune is worth 2 points, high resistance is worth 1 point, moderate resistance is worth 0 points, moderate infection is worth -1 point, and high infection is worth -2 points.

[0028] In a preferred embodiment of the present invention, a comprehensive evaluation is performed on each group of hybrid offspring based on plant height, maturity date, yield, and disease resistance, combined with an adaptability evaluation:

[0029] CS0 i =w1×H i +w2×M i +w3×P i +w4×F i +w5×A i Among them, w1, w2, w3, w4 and w5 are divided into

[0030] Do not indicate the weight of each indicator.

[0031] In a preferred embodiment of the present invention, in step S6, the hybrid offspring are sorted according to the comprehensive evaluation index of each group, and the top-ranked wheat varieties, along with their parent varieties, are selected for field trials under the same environmental conditions and field management.

[0032] In a preferred embodiment of the present invention, in step S6, a group of hybrid offspring with a comprehensive evaluation and Fusarium head blight resistance exceeding the parents by 10% are selected as new wheat varieties with high resistance to Fusarium head blight.

[0033] This invention addresses the shortcomings of the prior art and has the following beneficial effects:

[0034] (1) This invention provides a method for breeding new wheat varieties highly resistant to Fusarium head blight. The method involves selecting wheat varieties carrying different Fusarium head blight resistance genes for hybridization, and then rapidly propagating them in an artificial intelligence greenhouse while simulating environmental conditions in different ecological regions to assess the adaptability of the hybrid offspring. Furthermore, a comprehensive evaluation formula is used to score the hybrid offspring based on traits such as plant height, maturity, yield, disease resistance, and adaptability. The hybrid offspring with the best comprehensive evaluation performance, along with their parents, are then subjected to field trials to verify the degree of improvement in agronomic traits and Fusarium head blight resistance. By implementing the method described in this invention, not only can the breeding cycle be significantly shortened, but it also helps to breed new wheat varieties with stable agronomic traits and strong expression of disease-resistant genes, resulting in significant social benefits.

[0035] (2) This invention simulates environmental conditions in different ecological regions within an artificial intelligence greenhouse, enabling the evaluation of wheat varieties during non-natural growing seasons and simulating their performance under different environments. This allows for a more accurate assessment of the adaptability of each hybrid progeny. The adaptability evaluation based on this invention can screen out hybrid progeny with high adaptability. These hybrid progeny will exhibit better yield and Fusarium head blight resistance under different environmental conditions, i.e., stable expression of agronomic traits and disease resistance genes.

[0036] (3) This invention provides a comprehensive evaluation system for the breeding of wheat varieties by comprehensively evaluating hybrid offspring with different genetic backgrounds, gene combinations and environmental conditions. Through the comprehensive evaluation formula, combined with plant height, maturity, yield, disease resistance and adaptability traits, it can more intuitively evaluate the comprehensive performance of each hybrid offspring and provide accurate data basis for the breeding of new wheat varieties with high resistance to Fusarium head blight. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart of a preferred embodiment of the present invention for breeding new wheat varieties highly resistant to Fusarium head blight. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein. Therefore, the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0041] like Figure 1 As shown, this invention provides a method for breeding new wheat varieties highly resistant to Fusarium head blight, comprising the following steps:

[0042] S1. Select wheat varieties with different Fusarium head blight resistance genes as parents for crossbreeding;

[0043] S2. Hybridization is carried out in an artificial intelligence greenhouse to obtain the initial F1 generation, and the genotype is gradually purified through continuous self-crossing or backcrossing to obtain genetically stable hybrid offspring.

[0044] S3. Divide the artificial intelligence greenhouse into multiple simulated planting areas. Each planting area simulates the ecological conditions of different regions, including soil conditions, temperature and humidity.

[0045] S4. Based on the genetic background and disease-resistant gene combination of the hybrid offspring, the hybrid offspring in each group are grouped and then assigned to different planting cohorts. These planting cohorts are planted in different planting areas, and data on plant height, maturity, yield and disease resistance of the hybrid offspring in each cohort are collected.

[0046] S5. Based on the data collected in S4 and the environmental conditions of the planting area where each cohort is located, an adaptability evaluation is performed on each group of hybrid offspring, and then a comprehensive evaluation of each group of hybrid offspring is calculated by combining the data collected in S4.

[0047] S6. In the comprehensive evaluation, select several groups of hybrid offspring with the best performance and conduct field trials together with their parents. By comparing the comprehensive evaluation and disease resistance of the parents and corresponding hybrid offspring, select new wheat varieties with significant high resistance to Fusarium head blight.

[0048] In this embodiment, the preferred methods are to use the wheat-ciliad translocation lines NAURc001, Sumai 3, Wangshuibai, Yangmai 33 and Ningmai 9 as male and female parents respectively for pairwise hybridization, covering all possible hybridization combinations.

[0049] In this embodiment, the parents are assigned codes in sequence: A, B, C, D, E, and F. The hybridization groups are also assigned codes according to the order of the father and mother. For example, if NAURc001 is used as the father and Sumai 3 is used as the mother for hybridization, the code for this group is AB; if Wangshuibai is used as the father and NAURc001 is used as the mother for hybridization, the code for this group is CA. This code represents the genetic background of the hybrid offspring for subsequent tracing.

[0050] It is worth noting that these wheat varieties all contain different Fusarium head blight resistance genes: NAURc001 contains the Fusarium head blight resistance gene FhbRc1; Sumai 3 contains Fhb1 and Fhb2; Wangshuibai contains Fhb1, Fhb2, Fhb4 and Fhb5; Yangmai 33 contains Fhb1; and Ningmai 9 contains Fhb1.

[0051] The AI ​​greenhouse in step S2 is a modern greenhouse that utilizes artificial intelligence technology for crop growth environment control and management. This type of greenhouse can optimize crop growth conditions and improve crop yield and quality through automated and intelligent systems. This is existing technology and will not be elaborated further.

[0052] Step S2 involves hybridizing different parent wheat varieties using artificial pollination. Specifically, pollen is collected when the anthers of the male wheat mature, and then the pollen is transferred to the stigma of the female wheat to achieve fertilization.

[0053] Self-pollination of the F1 generation (involving cross-pollination between the pistils and stamens of the same plant) or backcrossing (involving hybridization between the F1 generation and one of the parents) is performed. The purpose of self-pollination and backcrossing is to ensure the stable expression of specific Fusarium head blight resistance genes in the offspring. Through several generations of self-pollination or backcrossing, combined with continuous selection and screening measures, the wheat genotype is gradually purified, reducing its heterozygosity, thereby cultivating genetically stable offspring. This process needs to be repeated for multiple generations until the genotype of the offspring reaches a genetically stable state. During this process, marker-assisted selection technology is used to accurately identify the expression of Fusarium head blight resistance genes in the hybrid offspring.

[0054] In this embodiment, rapid generation technology is used in the artificial intelligence greenhouse. Based on the 'speedbreeding' method proposed by Watson et al. (2018), and by using light conditions with a light flux density of about 550 μmol m-2s-1, a photocycle of 22h light + 2h darkness, and a culture temperature of 22℃ (light) + 17℃ (dark), combined with the method of early seed harvesting, the breeding efficiency of hybrid offspring and the purification speed of genotype are further improved, and the time cycle of hybridization breeding is significantly shortened.

[0055] Step S3 divides the artificial intelligence greenhouse into three regions, corresponding to the simulated northern winter wheat region, Huanghuai winter wheat region, and southwestern winter wheat region, and assigns codes to these three regions: Northern winter wheat region X, Huanghuai winter wheat region Y, and Southwestern winter wheat region Z.

[0056] The Northern Winter Wheat Region: Roughly located south of the Great Wall, east of the Minshan Mountains, and north of the Qinling Mountains and the Huai River, including all of Shandong Province, most of Henan, Hebei, Shanxi, and Shaanxi Provinces, eastern and southern Gansu Province, and northern Jiangsu and Anhui Provinces. This region has a continental climate, with an average annual temperature of 9–15℃, an average temperature of -10.7 to -0.7℃ in the coldest month, and extreme minimum temperatures reaching -30.0 to -13.2℃. The accumulated temperature ≥10℃ is around 4050℃, and the annual precipitation is 440–980 mm, with most areas receiving around 200 mm. Spring droughts are common, and in some years, autumn droughts are also severe.

[0057] The Huang-Huai winter wheat region is located in the middle and lower reaches of the Yellow River, bordering the northern winter wheat region to the north and northwest, and bounded to the south by the Huai River and the Qinling Mountains. It includes all of Shandong Province, most of Henan Province except for the Xinyang area, central and southern Hebei Province, and the areas north of the Huai River in Jiangsu and Anhui provinces. With a suitable climate, it is the region in my country with the most suitable ecological conditions for wheat growth, ranking first in both area and total yield among all wheat-growing regions, with relatively stable yields over the years.

[0058] Southwest Winter Wheat Region: Located south of the Qinling Mountains and the Huai River, including Sichuan, Chongqing, Yunnan, and Guizhou, this region primarily cultivates high-quality medium-gluten wheat. The region is rich in water resources and receives abundant natural rainfall, but the distribution is extremely uneven. In some areas, due to uneven seasonal rainfall, winter and spring rainfall is low, leading to frequent droughts.

[0059] In this embodiment, the specific simulation settings for the northern winter wheat region, the Huang-Huai winter wheat region, and the southwestern winter wheat region in the artificial intelligence greenhouse include:

[0060] In the northern winter wheat region: the average temperature is controlled between 9 and 15℃, and the simulated temperature of the coldest month is -10.7 to -0.7℃; the precipitation is set between 440 and 980 mm, and spring drought conditions are simulated. The frequency and amount of precipitation are controlled by artificial intelligence; brown soil is used as the soil type.

[0061] The Huang-Huai winter wheat region: the average temperature is controlled between 10 and 20℃, and the simulated temperature of the coldest month is -10.7 to 1℃; the annual precipitation is set between 600 and 1000 mm, focusing on simulating the concentrated precipitation in July and August, while setting moderate drought conditions in spring to reflect the seasonal distribution of precipitation in the region, and controlling the frequency and amount of precipitation through artificial intelligence; the soil type used is loess.

[0062] Southwest winter wheat region: The average temperature is set at 12-24℃, with the average temperature of the coldest month kept above 5℃; the annual precipitation is set at over 1000mm, especially in spring and summer, to simulate the region's high humidity and rainy climate, and the frequency and amount of precipitation are controlled by artificial intelligence; red soil is used as the soil type.

[0063] Step S4 involves dividing the offspring carrying different combinations of Fusarium head blight resistance genes into different groups based on the marker-assisted selection results of the hybrid offspring from step S2. Each group should have a uniform genetic background, and the number of plants in several planting cohorts within the same group should be equal. Marker-assisted selection is an existing technology, and the Fusarium head blight resistance genes possessed by NAURc001, Sumai 3, Wangshuibai, Yangmai 33, and Ningmai 9 all have corresponding molecular markers. The specific implementation process will not be elaborated further.

[0064] In this embodiment, the code assigned to each known Fusarium head blight resistance gene is shown in Table 1:

[0065] Table 1. Allocation of Gene Codes for Resistance to Fusarium Head Blight

[0066] code 01 02 03 04 05

[0067] It is worth noting that each cohort code combination is set as: genetic background + gene combination + planting area; for example, NAURc001 is used as the male parent and Sumai 3 is used as the female parent to hybridize and obtain the FhbRc1 and Fhb2 gene combination that is resistant to Fusarium head blight. The planting cohort code combination in the northern winter wheat area is AB0103X, which makes it easy to distinguish several cohorts and provides convenience for subsequent analysis and selection.

[0068] The disease resistance data in step S4 specifically refers to resistance to Fusarium head blight. It is preferable to use a single-flower drip inoculation method to inoculate and identify the polymers against Fusarium head blight, and to evaluate their resistance. This specifically includes the following steps:

[0069] Prepare a pure strain of Fusarium graminearum and culture it on a suitable culture medium to obtain sufficient mycelium or spores, and prepare a suspension of the strain.

[0070] Preparation of bacterial suspension: Conidia were extracted from the cultured bacterial strain and suspended in sterile water to prepare a bacterial suspension; the spore concentration in the bacterial suspension was determined by microscope and counting plate to ensure that the spore concentration in the bacterial suspension used for inoculation was 5×10^4 to 5×10^5 spores per milliliter.

[0071] When the hybrid offspring enter the flowering stage, use a micropipette or dropper to drip the bacterial suspension onto the opening of the wheat flower, and gently shake the flower to promote the invasion of pathogens and ensure the effectiveness of inoculation.

[0072] Three days to one week after inoculation, regularly observe and record the development of disease in wheat flowers and ears. Pay attention to recording the time of disease occurrence, severity, and affected parts of the wheat.

[0073] Based on the disease observation results, the disease severity of the hybrid offspring was graded from 0 to 4: 0 indicates no disease, 1 indicates slight damage, 2 indicates moderate damage, 3 indicates severe damage, and 4 indicates very severe damage. The frequency of each disease level in all plants in each cohort was recorded.

[0074] The severity level is set to 0%, 25%, 50%, 75%, and 100%.

[0075] Calculate the disease index Where: X i S is the number of plants with the i-th level disease. i D is the representative value of the severity of the i-th level disease. i It is the occurrence frequency (X) of the i-th level disease. i (Percentage of total plants), S maxIt represents the severity level of the disease at its most severe stage.

[0076] Based on the DI value, the resistance of hybrid offspring is divided into different levels, including: immune, highly resistant, moderately resistant, moderately susceptible, and highly susceptible.

[0077] The adaptation evaluation in step S5 includes the following steps:

[0078] S51. Calculate the average yield of all hybrid offspring in each planting area;

[0079] S52. Calculate the average Fusarium head blight resistance score of all hybrid offspring in each planting area;

[0080] S53, Adaptability score of each group of hybrid offspring Among them, Y ij D is the yield of hybrid offspring i in the j-th planting area; ij E is the Fusarium head blight resistance score of hybrid offspring i in the j-th planting area; j F is the yield score weight for the j-th planting area; j The disease resistance score weight for the j-th planting area; n is the total number of planting areas.

[0081] In this embodiment, j represents several planting regions: the northern winter wheat region, the Huang-Huai winter wheat region, and the southwestern winter wheat region; where E j Specifically, the yield scoring weights among the northern winter wheat region, the Huang-Huai winter wheat region, and the southwestern winter wheat region are 0.3, 0.4, and 0.3, respectively; F j Specifically, the weights for Fusarium head blight resistance scores among the northern winter wheat region, the Huang-Huai winter wheat region, and the southwestern winter wheat region are 0.3, 0.4, and 0.3, respectively. This embodiment emphasizes the importance of the Huang-Huai winter wheat region, using the performance of hybrid offspring in a simulated Huang-Huai winter wheat growing environment as the most important evaluation indicator.

[0082] This invention simulates environmental conditions in different ecological zones within an AI-powered greenhouse, enabling the evaluation of wheat varieties during non-natural growing seasons and simulating their performance under varying conditions. This allows for a more accurate assessment of the adaptability of each hybrid progeny. The adaptability evaluation based on this invention can screen for highly adaptable hybrid progeny, which exhibit better yield and Fusarium head blight resistance under different environmental conditions, demonstrating stable expression of agronomic traits and disease resistance genes.

[0083] In one embodiment, an adaptive evaluation of multiple disease resistances is conducted, and different disease resistances exhibit different behaviors under different environmental conditions, specifically:

[0084] Calculate the average disease resistance score of all hybrid offspring in each planting area;

[0085] Fitness score of each hybrid offspring

[0086] Among them, D ijk It is the resistance score of hybrid offspring i to disease k in the j-th planting area; F jk is the resistance score weight of disease k in the j-th planting area; m is the number of disease types considered; D ijk It is the resistance score of hybrid offspring i to disease k in the j-th planting area.

[0087] The disease resistances selected in this embodiment include resistance to Fusarium head blight, powdery mildew, sheath blight, and leaf rust.

[0088] It is worth noting that E j F and F jk Weights are determined using methods such as expert consultation, historical data analysis, and multi-objective optimization.

[0089] In this embodiment, the plant height, maturity period, yield, and disease resistance indicators of each group of hybrid offspring are scored and judged:

[0090] Plant height is the average plant height H of each group of hybrid offspring. i The scores are divided into four levels: 2 points for 80cm and below, 1 point for 80-85cm (inclusive), 0 points for 85-90cm (inclusive), and -1 point for over 90cm.

[0091] The maturity period is M, which is the average maturity period of each group of hybrid offspring. i The scores are divided into three levels, based on a control group: 1 point for early-maturing varieties, 0 points for equivalent varieties, and -1 point for late-maturing varieties.

[0092] The yield is the total yield P of each group of hybrid offspring. i The yield is divided into three levels: 1 point is awarded for yields of 580kg or more, 0 points are awarded for yields between 550kg and 580kg (inclusive), and -1 point is awarded for yields of 550kg or less.

[0093] Fusarium head blight resistance is the average resistance F of each hybrid progeny. i The test is divided into five levels: immune, high resistance, moderate resistance, moderate infection, and high infection. Immune is worth 2 points, high resistance is worth 1 point, moderate resistance is worth 0 points, moderate infection is worth -1 point, and high infection is worth -2 points.

[0094] Based on the plant height, maturity date, yield, and disease resistance of each group of hybrid offspring, and combined with adaptability evaluation, a comprehensive evaluation of each group of hybrid offspring was conducted:

[0095] CS0 i =w1×H i +w2×M i +w3×P i +w4×Fi +w5×A i Among them, w1, w2, w3, w4 and w5 are divided into

[0096] Let w1 represent the weight of each indicator, and w1+w2+w3+w4+w5=1.

[0097] In this embodiment, the weights w1, w2, w3, w4 and w5 used for comprehensive evaluation of each indicator are set to 0.1, 0.2, 0.3, 0.2 and 0.2 respectively.

[0098] This invention provides a comprehensive evaluation system for wheat variety breeding by comprehensively evaluating hybrid offspring with different genetic backgrounds, gene combinations, and environmental conditions. The comprehensive evaluation formula combines plant height, maturity, yield, disease resistance, and adaptability traits. It can more intuitively evaluate the overall performance of each hybrid offspring and provide accurate data for breeding new wheat varieties with high resistance to Fusarium head blight.

[0099] Step S6: Sort the hybrid offspring according to the comprehensive evaluation index of each group, select the top-ranked varieties and their parent wheat varieties, and conduct field trials under the same environmental conditions and field management.

[0100] The comprehensive evaluation in step S6 uses the formula: CS1 i =w6×H i +w7×M i +w8×P i +w9×F i The weights w6, w7, w8 and w9 used for comprehensive evaluation of each indicator are set to 0.15, 0.25, 0.35 and 0.25 respectively.

[0101] The CS1 value and Fusarium head blight resistance of each hybrid offspring group and its parents were compared, and several hybrid offspring groups that exceeded the parents in both values ​​were selected as new wheat varieties with high resistance to Fusarium head blight.

[0102] In this embodiment, the comprehensive evaluation CS1 value and Fusarium head blight resistance of a group of hybrid offspring both exceeded those of the parents by 10%, and they were selected as a new wheat variety with high resistance to Fusarium head blight.

[0103] In this embodiment, three groups of hybrid offspring were selected through the above steps S1 to S5 and named as sample 1, 2 and 3 according to the comprehensive evaluation ranking.

[0104] The genetic background and disease resistance gene combination of sample 1 are: NAURc001-Yangmai 33 (FhbRc1, Fhb1).

[0105] The genetic background and disease resistance gene combination of sample 2 are: NAURc001-Wangshuibai (FhbRc1, Fhb2, Fhb5).

[0106] The genetic background and disease resistance gene combination of sample 3 are: Wangshui Bai-Sumai 3 (Fhb1, Fhb2, Fhb4).

[0107] Samples 1, 2, and 3, along with their parents NAURc001, Yangmai 33, Wangshuibai, and Sumai 3, were subjected to field trials at the breeding innovation base of the Zhongken Seed Industry Science and Technology Innovation Center (within the territory of Shanghai Farm).

[0108] The tested varieties were arranged in a completely randomized block design with three replicates. Each plot was 0.02 mu (approximately 0.02 hectares), and the entire plot was harvested. Field management practices were slightly higher than local production standards. Experimental management included timely fertilization, pest control, and weeding, but no chemical control of diseases or use of plant growth regulators. All management measures (including sowing date, density, fertilization amount and method) were to be consistent across varieties and blocks within the same experimental site. The same management measures within the same replicate were to be completed on the same day. Effective protective measures were to be taken promptly during the experiment to prevent harm from humans, rodents, birds, livestock, and poultry.

[0109] The yields and scores of each variety in the field trials are shown in Table 1:

[0110] Table 1. Yield and scores of various varieties in field trials

[0111]

[0112] The comprehensive evaluation parameters for each variety in the field trials are shown in Table 2:

[0113] Table 2. Comprehensive Evaluation Table of Field Trials

[0114]

[0115]

[0116] Based on the above data, Sample 1 and Sample 3 performed well in the field trials. Their disease resistance and overall evaluation were greater than or equal to those of their parents. Furthermore, both of them met the high resistance standard for Fusarium head blight and can be used as new wheat varieties with high resistance to Fusarium head blight for subsequent new variety experiments or tests.

[0117] Based on the preferred embodiments of the present invention described above, those skilled in the art can make various changes and modifications without departing from the inventive concept. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for breeding new wheat varieties highly resistant to Fusarium head blight, characterized in that, Includes the following steps: S1. Select wheat varieties with different Fusarium head blight resistance genes as parents for crossbreeding; S2. Hybridization is carried out in an artificial intelligence greenhouse to obtain the initial F1 generation, and the genotype is gradually purified through continuous self-crossing or backcrossing to obtain genetically stable hybrid offspring. S3. Divide the artificial intelligence greenhouse into multiple simulated planting areas, which correspond to the simulated northern winter wheat region, Huang-Huai winter wheat region and southwestern winter wheat region respectively. Each simulated planting area simulates the soil conditions, temperature and humidity of the corresponding region. S4. Based on the molecular marker-assisted selection results, genetic background, and disease-resistant gene combinations of the hybrid offspring, group them so that each group of hybrid offspring has a uniform genetic background; assign each group of hybrid offspring to planting cohorts located in different simulated planting areas, with the number of plants in each planting cohort of the same group being equal, and collect data on plant height, maturity, yield, and Fusarium head blight resistance of the hybrid offspring in each planting cohort. S5. Calculate the average yield and average Fusarium head blight resistance score of all hybrid offspring in each simulated planting area, and calculate the fitness score A for each hybrid offspring using the following formula. i : ； in, It is a hybrid offspring In the Yields in a simulated planting area For all hybrid offspring of the combination, at the first Average yield in each simulated planting area; It is a hybrid offspring In the Fusarium head blight resistance scores in simulated planting areas For all hybrid offspring of the combination, at the first Average Fusarium head blight resistance score in each simulated planting area; It is the first The yield score weights for each simulated planting area; No. The disease resistance score weights for each simulated planting area; This is the total number of simulated planting areas; Then, by combining the data collected in S4, a comprehensive evaluation of each group of hybrid offspring is calculated. S6. In the comprehensive evaluation, select several groups of hybrid offspring with the best performance and conduct field trials together with their parents. By comparing the comprehensive evaluation and disease resistance of the parents and corresponding hybrid offspring, select new wheat varieties with significant high resistance to Fusarium head blight.

2. The method for breeding new wheat varieties highly resistant to Fusarium head blight according to claim 1, characterized in that: In S1, the wheat-cilia translocation lines NAURc001, Sumai 3, Wangshuibai, Yangmai 33 and Ningmai 9, which are resistant to Fusarium head blight, were used as male / female parents for pairwise hybridization.

3. The method for breeding new wheat varieties highly resistant to Fusarium head blight according to claim 1, characterized in that: In S4, the disease resistance data refers to resistance to Fusarium head blight, and the polymer is inoculated with and identified using a single-flower drip method to evaluate its resistance to Fusarium head blight. Fusarium head blight resistance is classified into different levels, including: immune, highly resistant, moderately resistant, moderately susceptible, and highly susceptible.

4. The method for breeding new wheat varieties highly resistant to Fusarium head blight according to claim 1, characterized in that: In S5, the plant height, maturity period, yield, and disease resistance indicators of each group of hybrid offspring are scored and determined: Plant height is the average plant height of each group of hybrid offspring. The scores are divided into four levels: 2 points for 80cm and below, 1 point for 80-85cm, 0 points for 85-90cm, and -1 point for 90cm and above. The maturity period is the average maturity period of each group of hybrid offspring. The scores are divided into three levels, based on a control group: 1 point for early-maturing varieties, 0 points for equivalent varieties, and -1 point for late-maturing varieties. Yield is the total yield of each group of hybrid offspring. The yield is divided into three levels: 1 point is awarded for yields of 590kg or more, 0 points are awarded for yields between 540kg and 590kg, and -1 point is awarded for yields of 540kg or less. Fusarium head blight resistance is the average resistance of each group of hybrid offspring. The test is divided into five levels: immune, high resistance, moderate resistance, moderate infection, and high infection. Immune is worth 2 points, high resistance is worth 1 point, moderate resistance is worth 0 points, moderate infection is worth -1 point, and high infection is worth -2 points.

5. The method for breeding new wheat varieties highly resistant to Fusarium head blight according to claim 4, characterized in that: Based on the plant height, maturity date, yield, and disease resistance of each group of hybrid offspring, and combined with adaptability evaluation, a comprehensive evaluation of each group of hybrid offspring was conducted: ,in, , , , and Each indicator represents its weight.

6. The method for breeding new wheat varieties highly resistant to Fusarium head blight according to claim 1, characterized in that: In S6, the hybrid offspring are ranked according to their comprehensive evaluation index, and the top-ranked varieties, along with their parent wheat varieties, are selected for field trials under the same environmental conditions and field management.

7. The method for breeding new wheat varieties highly resistant to Fusarium head blight according to claim 1, characterized in that: In S6, the overall evaluation and Fusarium head blight resistance of a group of hybrid offspring both exceeded those of the parents by 10%, and they were selected as a new wheat variety with high resistance to Fusarium head blight.

Images